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Bcl::Cluster: A method for clustering biological molecules coupled with visualization in the Pymol Molecular Graphics System

机译:Bcl :: Cluster:一种在Pymol分子图形系统中结合可视化的生物分子聚类方法

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Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.
机译:在生物学的各种应用中,聚类算法被用作数据分析工具。在蛋白质结构预测和虚拟高通量筛选方法中,聚类变得尤为重要。在蛋白质结构预测中,聚类用于构造成千上万个蛋白质模型的构象空间。在虚拟高通量筛选中,具有数百万个类药物分子的数据库是通过结构相似性来组织的,例如常见的脚手架。从分层聚类获得的树状树状图结构可以提供结果的定性概述,这对于集中详细分析非常重要。但是,在实践中,很难将树状图的特定组成部分直接与组成它的对象联系起来,并难以在树状图的二维范围内显示所有所需信息。当前的工作提出了一种称为bcl :: Cluster的分层聚集聚类方法。 bcl :: Cluster利用Pymol分子图形系统以图形方式描绘了三维图。这允许同时显示相关的生物分子以及有关簇和包含它们的成员的其他信息。

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